Systematics and symmetry in molecular phylogenetic modelling: perspectives from physics
Peter D Jarvis, Jeremy G Sumner

TL;DR
This review explores the application of mathematical physics techniques to probabilistic models in molecular phylogenetics, highlighting symmetries, invariants, and quantum analogies to improve evolutionary inference methods.
Contribution
It introduces the use of group theory, Lie algebras, and tensor invariants from physics to analyze and enhance phylogenetic models and inference techniques.
Findings
Identification of polynomial invariants for phylogenetic models
Application of quantum entanglement concepts to phylogenetics
Development of new invariants like the 'squangle' for tree discrimination
Abstract
The aim of this review is to present and analyze the probabilistic models of mathematical phylogenetics which have been intensively used in recent years in biology as the cornerstone of attempts to infer and reconstruct the ancestral relationships between species. We outline the development of theoretical phylogenetics, from the earliest studies based on morphological characters, through to the use of molecular data in a wide variety of forms. We bring the lens of mathematical physics to bear on the formulation of theoretical models, focussing on the applicability of many methods from the toolkit of that tradition -- techniques of groups and representations to guide model specification and to exploit the multilinear setting of the models in the presence of underlying symmetries; extensions to coalgebraic properties of the generators associated to rate matrices underlying the models, in…
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